Flood Risk Assessment Unit
Intoduction:
Flood Risk Assessment Unit (FRAU) was established as a part of organizational setup in Irrigation Department having vital role in flood forecasting and effective flood management in Punjab. The main objectives of FRAU include development of province-based run time flood monitoring and management system, acquiring, manipulating and management of complete set of information to evaluate expected discharge at a given time in the river reach of interest and estimating volume of a specific flood peak likely to pass on a specific location, identification of areas/villages that are likely to be inundated.
Development of Hydraulic and Hydrological Models of all the rivers and associated nullahs for flood risk assessment and early warning before the occurrence of flood events. Preparation of GIS maps and dissemination of inundation maps to stakeholder for better decision making and flood fighting and extraction of flood path and identification of areas/villages under risk of breach.
Organogram of FRAU:

Achievements of FRAU:
Key Achievements:
- Developed Floodplain demarcation maps of Punjab Province for floodplains of 100 years return period. Floodplain demarcation for medium and high peaks of Vidore, Chachar, Vehowa, Kaura and Sanghar hill torrents have also been developed.
- Flood Atlas 2022 developed for analysis of flood situation including mapping of contours of flood inundation areas under different volumes of river flow.
- Creation of GIS database including digitization of field data, stream networks, historic flood extents and flood infrastructure. Database was also standardized as (per standards of Punjab Government).
- Development of Hydrological model for Chenab River at Marala for the forecast of flood peak, using Global Precipitation Measurement (GPM) satellite and synoptic data. The model has predicted flood peaks in monsoon of 2018 with 90% accuracy. Development of Hydrological model of Nullah Deg and Palku, Aik Nullah and its calibration for flood events of 2018. Hydrological Modelling of Chenab (downstream of Marala Barrage), Jhelum and Indus Rivers, Bimber and Basenter Nullahs.
- Seasonal Catchment yield estimation for monsoon of Vidore and Chachar hill torrents (D.G. Khan) by using integrated approach of remote sensing, GIS and runoff model.
- Geospatial system for monitoring and evaluation of ADP Schemes on monthly basis.
- Watershed delineation of rivers and nallahs of Punjab and transboundary regions of India.
- GIS Based precipitation information system for Punjab Rivers and Indian catchments.
- Daily flood map for report of flood situation using MODIS satellite imagery during flood seasons.
- Flood forecasting using data from national and international metrological data. Issuance of flood warning to the concerned departments.
- Drainage Networks Pattern Analysis.
- Calibration of satellite rainfall data with observed ground data.
- Routing model with the influence of lateral flows of Nallahs.
- Identify location of small dams in Pothohar region.
- Seasonal Catchment yield estimation for monsoon of Vehowa, Kaura and Sanghar hill torrents (D.G. Khan) by using integrated approach of remote sensing, GIS and runoff model.
- Temporal analysis of Snow cover in the upper catchment of Chenab River for base flow. Temporal and spatial analysis of Snow cover and glacier extend in the upper Indus basin and study the impact of climate extremes on the flows of upper Indus basin.
Ongoing Task:
- Analyzing drainage networks’ patterns
- Acquiring historic flood extend imagery, Digitizing historic flood extents
- Calibrating satellite rainfall data with observed ground data.
- Incorporating lateral flows of Nallahs in routing models
- Temporal analysis of Snow cover in the upper catchment of Chenab River for base flow.
- Hydrological modeling of River Jhelum from downstream of Rasul Barrage to Khusab Bridge.
- Daily reporting of rainfall forecasts and flood predications.
Way Forward:
- Collaborate (currently underway) with Google International to develop an Artificial Intelegnece (AI) based flood forecasting model.
- Partner with LUMS (Centre for Water Informatics & Technology) to use Machine Learning (ML) techniques in water resource management and predicting flood events.
- Analyze and predict multi-category flood peaks’ duration and frequency at major rim stations in Punjab.
- Simulate hydrology of watersheds in Punjab region using a semi-distributed hydrological model (SWAT) and QGIS.
- Hydro-dynamic modelling of River Indus and its tributaries in Punjab using latest HEC-RAS 6.0.
- Develop flood hazard maps for Koh-e-Suleman Piedmont Plain Areas.
- Device a management plan for flash floods in hill torrents.
- Identify locations for flood water storage.
- Breaching Analysis at trimmu barrage by using 2D – Model (Hec - RAS).
- Upgrading Flood inundation maps at different flood frequency (Marala to Khanki).
Budget:
20
Contacts:
20